• In the first part of this series, we discussed how AI and machine learning can enhance marketing efforts by driving more intelligent interactions and campaigns, while at the same time boosting employee productivity and efficiency. Now let’s dive into three skills marketers should focus on to get the most of out these technologies:

    Critical Thinking

    Ever look in the mirror and think, dang, I’m a great critical thinker? OK, that’s weird, but the good news is this is exactly the trait you need to work with AI platforms. Employers value these skills: a study by SmartInsights found that those hiring in this area consider possessing “problem-solving and analytical skills” the highest priority when assessing candidates working with AI. While automated platforms can help efficiently execute programs, marketers will still need to develop those campaigns.
    Keep in mind that this technology is really about automating the mundane and tedious tasks, like building lists and developing basic messaging. AI can help manage martech complexity, but it takes a critical mind to realize how this will help optimize brand strategy and take it to the next level. It saves time for marketers and gives them more time to think of the big picture ideas and tasks.

    Provide the Right Data to Keep AI Programs on Track

    AI is far from being able to fully understand humans. It still needs people to determine when answers are unclear, and AI-driven analysis doesn’t make sense. For the best results, marketers should provide the technology with data sets that are accurate, complete, and large. Algorithms can’t tell if the data is wrong. If it receives incorrect data at the start, it will continue to evolve and learn based off the incorrect information.
    Jim Guszcza, U.S. chief data scientist of Deloitte Consulting, emphasizes that these “handoff” processes are still needed, and must be monitored by people in order for critical revisions take place and to ensure data accuracy. The continuing need for humans to maintain data accuracy exemplifies that we can’t rely on this technology to hand us all of the answers.

    Moreover, it’s important to recognize that human bias affects algorithms that collect and analyze data. To combat this, marketers can have their algorithms audited—yes, it’s a thing!

    Using Emotion to Guide the Customer Experience

    While asking the right questions to provide the right data is important, marketers must also trust their gut instinct to determine how to connect with their target audience. It’s important that they keep an eye on what they’re automating, because the best ideas will still come from people. Consumers want to engage with and buy from the brands that care about them, not just the ones that know a lot about them.

    Think of some of the most groundbreaking campaigns in recent history, such as REI’s #OptOutside and WestJet’s Christmas Miracle Campaign. An AI platform wouldn’t have come up with either of them. Because the technology can’t feel emotion, it doesn’t come close to human ingenuity and knowing the customer experience. This is reflected in data about consumer preference , as 33% believe AI won’t accurately recognize their preferences and don’t want to interact with it.

    It’s up to the marketer to determine what the customer wants and to help future customers know what they want.

    With the right skills, marketers can actually get ahead by using AI and machine learning. These technologies can help them focus on big picture items, but only if they hone the skills they need to make it work for them.

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